EA seeks to drive enterprise efficiency with its form-filling AI platform

As businesses strive to meet growing regulatory demands and maintain operational efficiency, completing diligence questionnaires remains one of the most tedious and error-prone tasks in B2B environments. EA Global AI Limited, trading as EA, is a SaaS enterprise provider that aims to emerge as a leader in this space. Unlike standard diligence software, EA has reportedly developed an intelligent data room concierge, automating the completion of diligence questionnaires regardless of format. The company believes this approach addresses longstanding challenges for B2B sellers, including revenue slippage caused by lengthy due diligence processes. 

Industry overview and challenges 

Companies today operate in a complex environment defined by rising costs, intense competition, and rapid technological advancement [1]. In this intricate environment, ensuring transparency and traceability across operations is required yet challenging without appropriate due diligence processes [2]. Business activities such as mergers and acquisitions, sales, along with Environmental, Social and Governance (ESG) compliance, may require ongoing due diligence programs [3]. Yet, standard due diligence processes — in the form of questionnaires — are associated with an over-reliance on manual methods. This practice has teams sifting through an abundance of data across documents, spreadsheets and email, resulting in errors and resource inefficiencies, particularly as organisations grow [4]​​. Overall, this further complicates the due diligence process [4].

However, Artificial intelligence (AI) is reportedly reshaping due diligence across various aspects of business, offering the potential to enhance efficiency and accuracy in organisational processes [5]. Although due diligence has traditionally been a complex and time-intensive process, experts assert that it is on the verge of transformation, with AI playing a critical role in automating operations, evaluating datasets, and delivering more accurate insights [5].

Additionally, as organisations generate and manage more data, AI technologies can be seen as increasingly important [6]. The global enterprise AI market, valued at $14.7bn in 2022, is projected to grow to $153.2bn by 2030 exhibiting a CAGR of 34% during the forecast period [7]. This growth is fuelled by the rising prominence of AI, as large language models like ChatGPT have entered mainstream use [8].

Therefore, processes requiring strict compliance such as customer due diligence— which previously relied on extensive manual verification— are gradually evolving with the integration of advanced algorithms. Moody’s research suggests that AI has the potential to streamline onboarding processes by automating tasks like background checks, credit assessments, and risk profiling [9].

Yet, enterprise organisations reportedly continue to grapple with the burdensome nature of due diligence questionnaires (DDQs), which are frequently required for ESG compliance, bids, tenders, or investor relations [10]. EA asserts that professionals in these functions are overwhelmed by repetitive disclosure requests. The company states that these questionnaires often arrive in varied formats — Excel, Word, and PDFs — necessitating time-consuming manual adaptations. According to the company, the process of fulfilling these requests often involves tedious copying and pasting from spreadsheet based ‘databases’ filled with previously answered questions. These labour-intensive steps can jeopardise deal timelines, damaging reputations and risking trust. EA observes that for companies, where minor delays may reportedly threaten millions in revenue, inefficiencies during diligence may create significant risk of “slippage”, or gaps between projected and actual revenue [11].

 

 

B2B sales operations are another area primed for significant improvement through AI-powered due diligence, according to EA. Research indicates that incomplete or flawed diligence process can derail deals [12], while manual diligence can divert time and energy away from strategic sales initiatives [13]. Sales representatives frequently redirect their focus to error-prone manual tasks instead of high-impact activities. Under the pressure to meet quotas, sales teams may introduce human error in their data entries, resulting in compliance risks. This may also disrupt financial performance evaluations, further emphasising the importance of diligence accuracy as a preventive measure [14].

The stakes are also high for tender submissions where precision and speed of completions often determine the success of a bid [15]. Additionally, even web-based ESG platforms like EcoVadis are also completed by manual copy-and-paste processes, including extensive documents and approval bottlenecks, according to EA. Furthermore, ensuring compliance with regulations such as the Corporate Sustainability Reporting Directive (CSRD) in the EU is integral to a company’s risk management and corporate social responsibility (CSR) strategies [16]. Non-compliance can result in fines and lost sales opportunities [17].

Therefore, adopting generative AI (GenAI) in due diligence is becoming essential to maintaining competitiveness and mitigating risks effectively [5]. Reportedly, EA’s solution is purpose-built to address these pain points, transforming diligence completion from a procedural bottleneck into an operational advantage. Its intelligent data room concierge automation is designed to relieve overstretched teams of repetitive tasks, empowering organisations to shift their focus to strategic opportunities.

Introducing EA

EA’s platform is positioned as a form-filling AI platform that automates the completion of diligence questionnaires. The company states it can automate the completion of these requests at scale, transforming processes that once took weeks into tasks that can be completed within minutes. Designed to handle the full spectrum of complex B2B diligence scenarios, it claims to offer greater accuracy, transparency, and scalability while minimising inefficiencies.

The company asserts that its GenAI-native platform transforms previously vulnerable processes into potential competitive strengths. For enterprises, EA claims it could allow them to mitigate revenue slippage and enhance operational agility. Reportedly, this transformation from manual to automated diligence completions represents a dramatic shift by eliminating not only organisational inefficiency but also the likelihood of human error — ensuring questionnaires are found, audited, and customised for specific diligence requests and disclosures in record time.

What does EA do?

EA declares its proprietary graph-based Retrieval-Augmented Generation (graphRAG) technology identifies precise responses for varying diligence scenarios. According to the company, the platform is designed to maintain accuracy while adapting responses to the diverse needs of stakeholders. Specifically, the company highlights that its platform is capable of automating responses for various diligence surveys, including carbon disclosure projects (CDP), EcoVadis, tenders, requests for information (RFIs) and DDQs.

Through its graphRAG technology, EA states it can identify the most appropriate answers, pulling from client-uploaded documents or previously approved responses. Then, the GenAI-native platform produces responses using natural language processing. Therefore, EA states its platform eliminates the need for manual searching, copying, and pasting, saving stakeholders up to 90% of the time they currently spend answering surveys.

The company also claims that responses can be shared throughout organisations, enabling a collaborative sign-off process. With a built-in answer approval engine, EA states its software workflow can allocate responses to the client’s subject-matter experts for review and enables four to six-eye approvals when necessary, according to regulation. According to the company, EA accommodates longevity management for approvals that face expiration and require renewal to remain valid.

Unlike free models or paid competitors on the market, EA reports that its platform has been trained on ESG data, ensuring that ESG-specific language nuances are recognised and responded to correctly. EA reports that its platform contains over 800,000 proprietary data points, has mapped over 3,200 ESG questions in its knowledge-graphs, and has scraped over 46,000 public sustainability disclosures of companies. Additionally, for robust data protection, EA asserts it uses a customised large language model that is hosted on infrastructure owned by the company.

The next steps 

Among its plans, EA reports it is looking to develop its sales, marketing, and customer success functions. The company has chosen to use Floww’s innovative infrastructure to facilitate its funding efforts and help it achieve its future goals.  

According to the company, 2024 saw EA conducting pilot programmes with 18 organisations. In 2025, the company aims to achieve zero-touch onboarding to enable its lead generation to scale. Furthermore, it seeks to achieve ISO27001 and SOC2 compliance by Q2 2025.

 

*Floww Markets Limited is a company authorised and regulated by the Financial Conduct Authority (FCA). Firm reference number 980098.  

 The information and imagery contained within this article does not represent the opinions of Floww. Floww does not have a view on opinions provided by EA Global AI Limited in this article and elsewhere where they may be expressed and is not responsible or liable for the information within this article.